Synchronized optimization of the logistics system of a tobacco high-bay warehouse under production task fluctuations

Abstract

Cigarette companies typically use a logistics system where semi-finished and finished tobacco high-bay warehouse storage areas are situated in close proximity to each other and connected to the trolley tracks. However, the fluctuations in production tasks, such as the insertion of new tasks, implementation of emergency orders, and cancellation of existing orders, might pose certain challenges to the production process, including a high storage capacity ratio and insufficient trolley transportation capacity. These challenges can further affect storage efficiency and continuous production capacity. To this end, this study proposes a synchronized optimization method for the logistics system of a tobacco high-bay warehouse. To address the problem of excessive storage capacity ratio, this study adopts a synchronized strategy for joint allocation of storage spaces in the two functional areas, a storage allocation model is developed and solved to improve storage efficiency. To address the problem of insufficient trolley transportation capacity, this study adopts a synchronized strategy of trolley redistribution in the two functional areas and a neural network model is used to predict the optimal number of trolleys, improving the overall transportation efficiency. The experimental results indicate that the proposed synchronized operation method can enhance production efficiency under production task fluctuations.